Research On Channel Estimation Of MIMO-OFDM System

As the rapid development of mobile communication systems and wireless LAN, higher demands for information transmission rate are increasing. A higher information transmission rate requires a higher channel capacity; multiple-input multiple-output (MIMO) systems can effectively increase the channel capacity without increasing the frequency bandwidth and improve the effectiveness and reliability of information transmission. Another challenge of high-speed wireless communication is finding the way to overcome the frequency-selective fading in channels. Orthogonal Frequency Division Multiplexing (OFDM) technology can overcome the frequency selective fading, MIMO-OFDM technology has become one of the main themes of the new generation mobile communication technology.The performance of wireless communication systems are constrained by the channel characteristics at a large extent. The paths between transmitter and receiver are complex and diverse. What is different from cable channels is that wireless channel has a lot of randomness, and it results in the attenuation of received signal amplitude, phase distortion and frequency distortion, so this is a great challenge in the performance of the receiver. At the receiver, the channel estimation is a very important part, and the accuracy of channel estimation will directly affect the performance of the entire communication system. In MIMO-OFDM communication system, every received signal is the superposition of a number of signals from different transmission antennas through different channels, which is more complex than the channel estimation in SISO communication systems, so the channel estimation technology is one of the key technologies in MIMO-OFDM communication system.The analysis of this dissertation is based on MIMO-OFDM wireless communication system simulation platform built by MATLAB. In the dissertation, the main features of mobile wireless communication channel are analyzed, and on this basis, the channel environment is simulated by MATLAB; space-time block coding, space-time trellis coding and space-frequency coding theory in MIMO system is briefly introduced and simulated by MATLAB in the MIMO-OFDM systems, and the performance of different encoding methods in different channel environments is discussed. On the basis of the first two aspects, the channel estimation based on training sequences and the channel estimation based on pilots are discussed. In the discussion of channel estimation based on training sequences, simulations of channel estimations based on LS algorithm, DFT algorithm, LMMSE algorithm, SVD algorithm and LMS algorithm are completed in COST207 standard channel model, and the performances of different algorithms are compared; and in the discussion of channel estimation based on pilots, simulations of channel estimations based on linear interpolation, Gauss interpolation, and cubic spline interpolation are completed in COST207 standard channel model, and the performances of different interpolations are compared. Based on the analysis of the channel capacity in MIMO systems with different numbers of antennas, the simulation is completed by MATLAB, the performances of different channel estimation methods in MIMO-OFDM system with two transmitters and two receivers and MIMO-OFDM system with four transmitters and four receivers are analyzed and compared.